Systems and methods for identifying and managing topical content for websites

ABSTRACT

Systems and methods are disclosed for identifying and managing topical content for websites. In accordance with one implementation, a method is provided for identifying and managing topical content for a website. The method may include determining a set of topics at a first level of popularity, determining a set of topics at a second level of popularity, and discounting the set of topics at the second level of popularity based on the set of topics at the first level of popularity to determine a revised set of topics for the second level of popularity. The method may also include managing the topical content based on the revised set of topics for the second level of popularity.

This is a continuation of U.S. patent application Ser. No. 13/205,172,filed on Aug. 8, 2011 (now allowed), which is expressly incorporatedherein by reference in its entirety.

BACKGROUND Technical Field

The present disclosure relates generally to systems and methods foridentifying topics and managing content, such as content for a website.More specifically, and without limitation, the present disclosurerelates to systems and methods for identifying topical content andmanaging the content for presentation on one or more websites.

Background Information

Currently, newspapers, magazines, and other publishers of timely textualand visual content are increasingly competing with online websites forthe public's attention. Online websites that generate content (so-called“content sites”) often employ writers or bloggers to generate articles,podcasts, videos, and other content regarding topics that are popular atthe moment. This concept is sometimes referred to as trending. Thesecontent sites face challenges in generating the quantity and diversityof content desired by the public, while keeping a website's navigationalstructure topical, which is necessary to obtain sufficient web trafficand associated advertising revenue.

Some types of online content can have a low shelf-life, in that it canbe rendered out-of-date by, for example, current events or newconventional wisdom. In addition, online content faces tremendous levelsof competition. As a result of the fierce competition for onlinecontent, it is important for providers of online content to generatevery large volumes of content and manage the content to keep theirwebsite(s) fresh. It can be useful to continuously generate largeamounts of content about a topic to ensure that it is timely andup-to-date, as well to ensure that such content is distributed anddisplayed throughout the Internet, where it is likely to be consumed byonline users. But, it is also important that the navigational structureof a website can rapidly change to accommodate shifts in the popularityof topics, so the website can stay fresh and so that the rapidlygenerated content can be presented to the user in a topical, organizedmanner.

In view of the foregoing, there is a need for improved systems andmethods for identifying and managing topical content for websites. Thereis also a need for improved systems and methods that automaticallymanage the presentation of topical content, including by organizingand/or updating the navigational structure of a website.

SUMMARY

One aspect of the disclosure relates to a computer-implemented methodfor identifying and managing topical content for a website. The methodmay comprise determining a set of topics at a first level of popularity.The method may further comprise determining a set of topics at a secondlevel of popularity. The method may further comprise discounting the setof topics at the second level of popularity based on the set of topicsat the first level of popularity to determine a revised set of topicsfor the second level of popularity. The method may also comprisemanaging the topical content based on the revised set of topics for thesecond level of popularity.

Another aspect of the disclosure relates to a device for identifying andmanaging topical content of a website. The device may comprise at leastone processor; and a storage device storing a set of instructions, thatwhen executed by the at least one processor, perform a method. Themethod may comprise one or more of determining a set of topics at afirst level of popularity; determining a set of topics at a second levelof popularity; discounting the set of topics at the second level ofpopularity based on the set of topics at the first level of popularityto determine a revised set of topics for the second level of popularity;and managing topical content based on at least the revised set of topicsfor the second level of popularity.

Consistent with another aspect of the disclosure, the method or devicemay be used to update a navigational structure of a website based on thedetermined popularities.

Additional aspects of the present disclosure relate tocomputer-implemented systems and computer-implemented media forautomatically organizing a navigational structure, as further describedherein.

Before explaining exemplary embodiments of the present disclosure, it isto be understood that the disclosure is not limited in its applicationto the details of construction and to the arrangements of the componentsset forth in the following description or illustrated in the drawings.The disclosure is capable of embodiments in addition to those describedand of being practiced and carried out in various ways. Also, it is tobe understood that the phraseology and terminology employed herein, aswell as in the abstract, are for the purpose of description and shouldnot be regarded as limiting.

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate certain embodiments of thedisclosure, and together with the description, serve to explain theprinciples of the disclosure.

As such, those skilled in the art will appreciate that the conceptionupon which this disclosure is based may readily be utilized as a basisfor designing other structures, methods, and systems for carrying outthe several purposes of the present disclosure. It is important,therefore, to recognize that the claims should be regarded as includingsuch equivalent constructions insofar as they do not depart from thespirit and scope of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The following figures are used to describe exemplary features andembodiments related to the present disclosure. In the figures:

FIG. 1 depicts an exemplary system environment for practicingembodiments consistent with the present disclosure;

FIG. 2 depicts a flowchart of an exemplary process for practicingembodiments consistent with the present disclosure;

FIG. 3 depicts an exemplary relationship between two levels ofpopularity;

FIG. 4 depicts a flowchart of an exemplary process for determining atopic popularity, consistent with embodiments of the present disclosure;

FIG. 5A depicts an exemplary topic area, consistent with an embodimentof the present disclosure;

FIG. 5B depicts an exemplary topic area, consistent with an embodimentof the present disclosure;

FIG. 5C depicts an exemplary layout of a webpage of a website,consistent with an embodiment of the present disclosure;

FIG. 5D depicts an exemplary menu, consistent with an embodiment of thepresent disclosure;

FIG. 5E depicts an exemplary structure of a website, consistent with anembodiment of the present disclosure; and

FIG. 6 depicts a flowchart of an exemplary process for determining abreaking topic, consistent with an embodiment of the present disclosure.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments of thedisclosure, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

Embodiments of the present disclosure relate to identifying and managingtopical content for a website, including online electronic contentgenerated by users, which is often referred to as “user-generatedcontent” (“UGC”). Topical content may generally include any type orcombination of text, images, audio, video, or computer programs. Forexample, topical content may include articles, blog posts, photos,recordings, videos, music, audio tracks, software, and/or games createdby anyone in the world. In one embodiment, it may be desirable for usersto submit topical content to a network where it may be analyzed,manipulated, and/or distributed throughout the Internet. Althoughreferred to interchangeably as “topical content,” “electronic data,”“online content,” or “UGC,” such content may or may not be associatedwith the Internet. For example, content may be created, analyzed, and/ordelivered over any network, such as a mobile network, a cable televisionnetwork, a satellite network, or a device network.

FIG. 1 illustrates an exemplary system environment 100, consistent withthe disclosed embodiments. As further disclosed herein, environment 100may be used to perform various functions and methods for identifying andmanaging content, consistent with the present disclosure. The methods orprocesses performed in or with environment 100 may improve Internetusers' online experiences, increase the amount and quality of relevantonline content, and/or maximize network web traffic and advertisingrevenue.

As shown FIG. 1, environment 100 may include one or more servers 104,one or more user devices 101 and 102, and/or one or more databases 103.As further shown in the drawing, the components of FIG. 1 maycommunicate with one another via an electronic network 105, such as theInternet. In one embodiment, electronic network 105 comprises acollection of networks, such as wired and/or wireless networks.

Server 104 may be implemented with one or more computing systems and beassociated with an entity that delivers or otherwise makes electroniccontent and/or advertisements available over electronic network 105. Forexample, server 104 may be associated with an electronic contentprovider, an electronic advertisement provider, a search engine, anInternet Service Provider (ISP), a mobile service provider, an onlineretailer, or any other entity concerned with distributing electroniccontent and/or advertisements over electronic network 105. In oneembodiment, the server 104 may provide one or more content web pages,like AOL®, Google®, a news company (e.g., The Washington Post®, CNN®,Fox News®), a blog site, a social networking site, or any other companythat attracts the web traffic of users devices 101 and 102 to viewcontent on its web pages.

Moreover, server 104 may include one of more processors 104-1. Processor104-1 may include one or more hardware computer microprocessors forprocessing data according to a set of programmable instructions or asoftware modules 104-3 stored in memory 104-2 to perform the disclosedprocesses of sever 104. The functions of each processor may be providedby a single dedicated processor or by a plurality of processors. Inaddition, each processor may be a general-purpose processor or aspecial-purpose microprocessor configured to perform the disclosedfunctions of server 104.

Memory 104-2 may include any type of random-access memory (RAM) orread-only memory (ROM) embodied in a physical computer-readable storagemedium. Memory 104-2 may contain computer program instructions which,when executed by processor 104-1, cause the processor to perform thedisclosed processes of server 104.

In one embodiment, server 104 may include one or more servers or modulesfor organizing a website (not shown). The modules may use data 103-1stored in one or more databases 103 to organize the website structure.Database 103 may communication with server 104 over electronic network105, or may be directly connected to or located within server 104. Data103-01 may be distributed across multiple databases 103. The data 103-01may include content that server 104 includes in a website that isprovided to user device 101 or user device 102. The data 103-01 may alsoinclude user demographic information, user interest information,geographical information, and/or information relevant to personalizing awebpage.

Server 104 may control the display of electronic content at desiredtimes to desired user devices 101 and 102 on desired web pages so as tomaximize user experiences and/or advertising revenue. For example,topics of the webpage may be selectively matched in real-time based onthe identify of a user of device 101 or 102, a website/link/contentrequested by the user, time of day, geographic location, web history,preferences, and/or other information. Server 104, and/or one or more adservers (not shown) may serve ads based on contextual targeting ofwebsites, search results, advertiser information and/or user profileinformation. Such ad servers or server 104 may be configured to generatebehavioral logs, leadback logs, click logs, action logs, conversionlogs, and/or impression logs, based on users' interactions with websitesand/or ads which may be later used to determine a set of topics toinclude in the webpage.

User devices 101 and 102 may include a desktop computer, laptopcomputer, personal digital assistant (“PDA”), smartphone, mobile device,Internet-enabled television, automobile, or home, or any other mobile orelectronic device configured to access the electronic network 105. Userdevices 101 and 102, or their users, may or may not have an existingrelationship to server 104. Thus, the term “user” may refer to, forexample, any consumer, viewer, or visitor of a web page or website, andcan also refer to the aggregation of individual users into certaingroupings. References to users “viewing” content and/or ads is meant toinclude any presentation, whether visual, aural, tactile, or acombination thereof. In another embodiment, users may be a subset ofInternet users defined by their membership in a network associated withserver 104. For example, users may be provided with a username andpassword by which they may log-in to a network website. The network mayretain a set of attributes associated with each user, in a searchableprofile. The attributes may reflect the user's interests and incorporatecharacteristics that impact content and advertisement selection,purchasing, and/or other online behavior. Attributes may be createdbased on user data, such as impression history, click history, purchasehistory, demographic data, submission history, preferences, etc., any ofwhich may be user-supplied.

System 100 may further include one or more search engine systems (notshown). Search engine may include one or more server computersconfigured to parse or crawl textual data of content web pages onelectronic network 105, to index and store the textual data, and/or tosearch the indexed textual data based upon requests from users. In someembodiments, search engine systems may be standalone search enginesproviding a home page with a “query bar” into which users 106 may type akeyword query, like AOL®, Google®, or Yahoo®. Upon receipt of a keywordquery, search engine systems may search through the stored indices forweb pages on electronic network 105 that include, reference, and/or aretagged by the query keyword (i.e., so-called “hits”). In otherembodiments, search engine systems may include search engines integratedwith certain websites, such as news sites, social networking sites, or ablog sites. In such an embodiment, the search engines may parse, index,and search only web pages of the particular website with which thesearch engines are associated. Regardless of their embodiments orimplementations, search engine systems may also employ conventionalranking and relevancy algorithms to determine which web page resultswill be most relevant to the query keyword entered by users, and mayreturn search results as a list of hits, including a Uniform ResourceLocator (URL) link directing users to each web page hit, in a sequencebased on relevancy.

Search engine systems may maintain and store search results history, forexample, in an associated memory or data storage device. When a userprovides a keyword query to a search engine system, it may update thesearch results history with an entry containing information regardingthe query, as well as the search results returned to the user. Thesearch engine system may supply user selection information, along withinformation identifying the user or characteristics of a user, forstorage in database 103.

System 100 may further include one or more content collection systems(not shown). Content collection systems may collect and store digitalcontent—such as articles, blog entries, photos, videos, etc—for storagein a database, such as database 103. Content collection systems maycollect the content by scraping or crawling electronic network 105, asdiscussed above, or by receiving data from one or more feeds (e.g., theAssociated Press® news feed or Twitter®).

FIG. 2 illustrates a flowchart of an exemplary process, consistent withembodiments of the present disclosure. The exemplary process of FIG. 2may be implemented for automatically identifying and managing topicalcontent. In step S201, one or more devices may collect electronic data,such as electronic content. The one or more devices may include server104, user devices 101 or 102, and/or any other device capable ofprocessing electronic data. The collected data may include news,articles, blog entries, social media data, emails, Twitter® entries, orthe like. The one or more devices may collect the electronic data by oneor more of scraping, crawling a network, subscribing to one or more datafeeds, data logging, etc. The collected data may include one or moretags, keywords, categories, or other information from which a topic canbe determined. The one or more devices may store the collected data,and/or any associated tags, keywords, categories, or other metadata, indatabase 102.

In step S202, a device, such as server 104, may determine a popularityof one or more topics. A topic popularity may be determined based on oneor more factors, such as time, location, attributes or user device 101and/or 102, or attributes of users of device 101 and/or 102. In oneembodiment, a device may determine topic popularity by determining atopic of one or more pieces of the collected data. The device mayfurther determine topic popularity by maintaining a count of each topicfound in the collected data. One manner for determining the count mayinclude running one or more queries on the collected data. For example,in one embodiment, a search engine for network 105 may receive a queryrelating to one or more topics or keywords, and the number of resultsreturned may be used to determine a topic popularity.

Topic popularity may be determined based on different attributes. In oneembodiment, the attributes may be at different levels of popularity. Forexample, FIG. 3 depicts attributes having two levels of popularity, ahigher level of popularity 301 and a lower level of popularity 302.While FIG. 3 depicts two levels of popularity, three or more levels ofpopularity may be used. For example, popularity may be determined basedon a geographic context, an entity context, and/or a temporal context.

In a geographic context, the higher level of popularity 301 may be aspecific country or region of the world, and the lower level ofpopularity 302 may be a state, county, city, or town within the specificcountry or region of the world. In an entity context, the higher levelof popularity 301 may be a university or company, and the lower level orpopularity 302 may be a college or division within the university orcompany. In a temporal context, the higher level of popularity 301 maybe a month or year, and the lower level of popularity 302 may be a dayor week within the month or year.

FIG. 4 depicts a flowchart of an exemplary process consistentembodiments of the present disclosure. The exemplary process of FIG. 4may be implemented to determine a topic's popularity at the lower levelof popularity 302. First, in step S401, one or more devices, such asserver 104, determine a popularity of one or more topics at the higherlevel of popularity 301. As discussed above, the popularities may bedetermined based on one or more of the attributes or contexts indicatedabove. The popularities may also be determined based on one or morestatistics captured by server 104, the search engine, or one or moreother devices that monitor activity on electronic network 105. Forexample, popularity of a topic may be based, at least in part, on thenumber of times a user related to popularity level 301 and/or 302selects an article for a particular topic.

In step S402, one or more devices, such as server 104, may determine atopic's popularity at the lower level of popularity 302. This may beachieved in a similar manner to determining the popularity at the higherlevel of popularity, as discussed above. Then, in step S403, the one ormore devices may discount a topic's popularity at the lower level ofpopularity. This may be achieved by using, for example, an algorithmbased on KL divergence, the Bayes probability theorem, or statisticalmodeling. As an example, Barak Obama may be very prevalent in newarticles across the United States during the election, so he may not beidentified as a topic that is specifically popular in a particular smalltown or city in the United States. However, if a topic pertaining to aparticular issue is prevalent in the small town or city, but not theUnited States in general, that topic, even if the articles mention BarakObama, may still be included in the identified topics. As anotherexample, Osama bin Laden may be written about a lot globally (e.g.,mentioned in 50% of articles). In San Francisco, he may also beenwritten about a lot as well, but this is not specific to San Francisco.For example, in San Francisco, Osama may be mentioned in 45% ofarticles. In contrast, Barry Bonds may be mentioned in 30% of SanFrancisco articles, but he may only be mentioned in 1% of articlesglobally. Accordingly, Osama would be discounted so that Barry Bonds isdetermined to be a more popular topic in San Francisco.

Returning to FIG. 2, once the topics and topic popularities aredetermined, the one or more devices, such as server 104, may be used tomanage topical content for website(s). Managing topical content mayinclude controlling the presentation of one or more pieces of topicalcontent on a website, by selecting content to be displayed, a locationat which to display topical content, generation of one or more contentareas in which to display the topical content, and/or determining whenor to whom the topical content will be displayed based on, for example,the determined popularity of the content. Managing topical content mayalso include generating or updating a navigational structure and/ortaxonomy of a website. In one embodiment, generating or updating anavigational structure may include generating or updating one or morecontent, linking, or menu areas, such as on a webpage. Generating orupdating a navigational structure may further include generating orupdating one or more menus, such as a menu bar, a dropdown menu, a popupmenu, etc. of a website. Embodiments for generating or updating ataxonomy of a website may be implemented using similar techniques.

Consistent with one embodiment, FIG. 5A depicts an exemplary element500-A for including in a webpage. Element 500-A may be, for example,associated with a topical news area on a webpage. As shown in FIG. 5A,exemplary element 500-A is an element that includes one or more topics502-A that are determined to be popular for the local area of a user ofuser device 101 or 102. By way of example, in a small farming town ofthe user, people may be particularly concerned with a politician'spositions on farm grants, Emma Thompson may have just been electedmayor, and the local factory may have been in the news due to possiblelayoffs. One or more devices, such as server 104, may determine todisplay element 500-A in response to data received about the user'slocality. This information may be received based on one or more piecesof information entered by a user, an identifier used to access thewebpage, the user device 101 or 102 used to access the webpage, GPScoordinates, an IP address of user device 101 or 102, a user profile,etc. Instead of, or in conjunction with, displaying the topics, one ormore pieces of the electronic content, or a portion thereof, may bepresented in element 500-A. Element 500-A may also include a heading501-A, indicating its level of popularity, such a “LOCAL” or a nameassociated with the level of popularity (e.g., a town name, the name ofa group or organization, etc.). In one embodiment, an element pertainingto the higher level or popularity may also be displayed. In anotherembodiment, one or more content areas for the topics may be generatedfor individual ones of the topics. The content areas for the individualareas may include one or more pieces of electronic content pertaining tothe topic associated with the content area. The topics 502-A may behyperlinks or other elements that allow interaction with a user andaccess to relevant information. For example, a user may interact withtopics 502-A by mousing-over, clicking, touching, speaking the name of,scrolling to, or otherwise indicating a desire to select a particulartopic. Based on the user interaction, the user may navigate to one ormore windows or pages of content relating to the identified topics.These one or more pages may be created based on the identification ofpopular topics as discussed above. For example, the identification of apopular topic may cause a taxonomy of a website to include one or morecontent pages for the identified topics. The pages may be pre-generated,static pages or be dynamically generated. For example, the may begenerated based on running one or more database queries or by retrievingdata from one or more data feeds.

Once a page is generated, the page may be cached, such that the page maybe retrieved for some predetermined amount of time without have to rerunthe one or more database queries or reparse the data feed forinformation. The one or more database quires or data feeds may bepredetermined or generated based on the topics determined above.

Content may be stored in a database along with an indication of one ormore topic to which it relates. Accordingly, populating the website mayinclude query the database for content pertaining to a particular topic.The database may also store other information pertaining to the contentthat may be used in the query, such as the data on which the content wascreated or published, the number of times the content has been accessed,a rate by which the content is accessed, etc. Accordingly, populatingthe website may include retrieving current and/or popular content.

In response to determining a topic, one or more data feeds may begenerated based on the topic. The data feeds may include the content oridentifiers of content that is collected for the determined topic. Thedata feeds may be, for example, an XML data feed, such as an RSS datafeed. The data feeds may be generated, for example, by running one ormore queries, scraping content, or receiving content submissions.

FIG. 5B depicts another exemplary element 500-B, consistent with anembodiment of the present disclosure. Element 500-B may be, for example,a topical content area for including in a webpage. In element 500-B, thetopic of the content area may be indicated, such as by heading 501-B(e.g., “Farm Grants”). In element 500-B, content having the topicidentified by heading 501-B may be included, such as articles 502-B. Thecontent having the topic may also include, for example, one or morevideos, audio files, text files, and/or pictures. For example, one ormore thumbnail images corresponding to articles 502-B. The articles502-B may include hyperlinks or other elements that allow interactionwith a user and access to relevant content or information. In addition,element 500-B may be generated based on running on or more queries orreading a data feed, as discussed above.

FIG. 5C depicts an exemplary layout of a webpage 500-C of a website,consistent with an embodiment of the present disclosure. The webpage500-C may include one or more elements, such as elements 501-C to 506-C.Elements 501-C to 506-C may include one or more navigational elements,such as a menu, hyperlinks, etc. Elements 501-C to 506-C may include oneor more advertising elements, such as an image advertisement, a videoadvertisement, an interactive advertisement, etc. Elements 501-C to506-C may include one or more content areas for displaying content, suchas textual content, audio and/or video content, etc. —including, forexample one or more new articles. Elements 501-C to 506-C may includeelements 500-A and/or 500-B, as discussed above. Consistent with someembodiments, interacting with topics 502-A or articles 502-B may cause anew webpage or window to be loaded or one or more of elements 501-C to506-C to present content to a user.

One or more devices, such as web server 104, may dynamically orpre-generate elements 501-C to 506-C based on the determined topicsand/or the content collected for the determined topics.

FIG. 5D depicts an exemplary menu 500-D for a website, consistent withthe present disclosure. Menu 500-D may include one or elements 501-D to504-D. Menu 500-D may also include one or more sub-elements 501-D1 to501-D4. Menu 500-D may be updated based on the determination of topics.For example, elements 501-D to 504-D and/or sub-elements 501-D1 to501-D4 may be updated based on the determined topics. For example,elements 501-D to 504-D and/or sub-elements 501-D1 to 501-D4 may beupdated to present the determined topics. User interactions withelements 501-D to 504-D and/or sub-elements 501-D1 to 501-D4 may furthercause a webpage or window relating to a topic to be displayed, or one ofelements 501-C to 506-C to be updated to present content relating to aselected topic.

One or more devices, such as web server 104, may dynamically orpre-generate elements 501-D to 504-D and/or sub-elements 501-D1 to501-D4 based on the determined topics and/or the content collected forthe determined topics. As will be appreciated, the arrangement andnumber of elements in depicted in FIG. 5D is exemplary and otherarrangements and numbers of elements can be used, consistent with theteachings of the present disclosure.

Consistent with one embodiment, one or more devices, such as server 104,may use the identified topics to generate or update a taxonomy for awebsite. For example, one or more devices, such as server 104, maydynamically generate one or more sub-sections based on the identifiedtopics or topical content. This may be achieved by issuing one or morequeries upon receiving a request for a webpage. The website structuremay also be updated by manipulating one or more documents defining awebsite structure based on the determined topics. For example, FIG. 5Edepicts and exemplary document 500-E defining a website structure. Thestructure defined in document 500-E may be updated to reflect thedetermined topics. In one embodiment, the navigational structure ortaxonomy of the website may be updated based on a combination ofupdating document 500-E and issuing dynamic queries upon receiving arequest for a webpage. This may be achieved by first retrieving allrelevant all relevant documents for a give topic (e.g., San FranciscoNews). For a given result set, after applying relative entropy ordiscounting, a set of subjects and/or people that are popular may bedetermined, and each member of the set may have a lot of news associatedwith it. Accordingly, a position in the navigational structure may becreated for every item in the set.

Consistent with additional embodiments of the present disclosure, FIG. 6depicts a flowchart of an exemplary process for determining breakingnews or content. The breaking news may be displayed in a breaking newsarea of the webpage, or in a breaking news area for one of the levels ofpopularity 301 and 302. In step S601, one or more devices may determinethe topics for a level of popularity 301 and 302 at a first time period.In step S602, the one or more devices may determine the topics for thelevel of popularity 301 and 302 at a second time period. In step S603,the topics during the first time period and the second time period arecompared to determine one or more breaking topics. For example, this maybe achieved by applying relative entropy against two different timeperiods to determine what topics are new and interesting. For example,in San Francisco the determined popular topics may have included majortopics in months 1-4. However, in month 5, when the query is rerun, thetopic fashion may become more prominent than in the past. This maycause, for example, “fashion” to be deemed a breaking topic. Over time,“fashion” may become a major topic or it may disappear from popularity.

One skilled in the art will appreciate that computer programs forimplementing the disclosed methods may be stored on and/or read fromcomputer-readable storage media. The computer-readable storage media mayhave stored thereon computer-executable instructions which, whenexecuted by a computer, such as server 104, cause the computer toperform, among other things, the processes disclosed herein. Exemplarycomputer-readable storage media may include magnetic storage devices,such as a hard disk, a floppy disk, magnetic tape, or another magneticstorage device known in the art; optical storage devices, such asCD-ROM, DVD-ROM, or another optical storage device known in the art;and/or electronic storage devices, such as EPROM, a flash drive, oranother integrated circuit storage device known in the art.Computer-readable storage media are distinct from computer-readabletransmission media (i.e., transitory signals). The computer-readablestorage media may be embodied by or in one or more components ofenvironment 100.

One skilled in the art will further realize that the processesillustrated in this description may be implemented in a variety of waysand may include multiple other modules, programs, applications, scripts,processes, threads, or code sections that may all functionallyinterrelate to accomplish the individual tasks described above. Forexample, it is contemplated that these programs modules may beimplemented using commercially available software tools, using customobject-oriented code written in the C++ programming language, usingapplets written in the Java programming language, or may be implementedas with discrete electrical components or as one or more hardwiredapplication specific integrated circuits (ASIC) custom designed for thispurpose. In addition, the disclosure may be implemented in a variety ofdifferent data communication network environments and may use software,hardware, or a combination of hardware and software to provide thedisclosed functions.

The many features and advantages of the present disclosure are apparentfrom the detailed specification, and thus, it is intended by theappended claims to cover all such features and advantages of thedisclosure which fall within the true spirit and scope of thedisclosure. Further, since numerous modifications and variations willreadily occur to those skilled in the art, it is not desired to limitthe disclosure to the exact construction and operation illustrated anddescribed, and accordingly, all suitable modifications and equivalentsmay be resorted to, falling within the scope of the disclosure.

What is claimed is:
 1. A computer-implemented method for providingtopical content on a website for users, the method comprising thefollowing operations performed by one or more processors: retaining, ina database, attributes of a plurality of users, wherein the attributescomprise at least one of: an impression history, a purchase history, aconversion history, and/or user preferences; associating a plurality ofusers with a plurality of factors including the attributes; associatingcollected electronic content with a plurality of topics; determininglevels of popularity corresponding to combinations of the factors andthe topics based on the factors including the attributes, wherein thelevels of popularity include a higher level and a lower level;receiving, from a device of a first user, a content request associatedwith a first one of the factors; parsing one or more websites forcontent associated with the request; caching the one or more parsedwebsites; determining, based on the popularity of the topics in thehigher level, one or more discounted levels of popularity correspondingto the popularity of the topics in the lower level and the first one ofthe factors; managing the topical content based on the one or morediscounted levels of popularity for the first one of the factors andfurther generating one or more content areas in which to display thetopical content; and generating instructions to present, on the website,one or more pieces of the managed topical content in the generated oneor more content areas; wherein managing the topical content comprisesupdating one or more navigational menus and links of the website basedon the discounted levels of popularity for the first ones of thefactors, and wherein generating the instructions includes generatinginstructions to update the one or more navigational menus and links ofthe website.
 2. The computer-implemented method of claim 1, whereindetermining levels of popularity comprises: receiving, from theplurality of users, selections of content from the collected electroniccontent; and determining the levels of popularity, for combinations ofthe topics and the factors, based on the numbers of times usersassociated with the factors selected content associated with the topics.3. The computer-implemented method of claim 1, wherein determiningdiscounted levels of popularity comprises: identifying a second one ofthe factors; and calculating the discounted levels of popularity basedon (i) the levels of popularity corresponding to the combination of thetopics and the first one of the factors, and (ii) the levels ofpopularity corresponding to the combination of the topics and the secondone of the factors.
 4. The computer-implemented method of claim 3,wherein the second one of the factors encompasses the first one of thefactors.
 5. The computer-implemented method of claim 3, wherein at leastone of the first one of the factors and the second ones of the factorsis time.
 6. The computer-implemented method of claim 3, whereindetermining the discounted levels of popularity comprises calculatingthe discounted levels of popularity using at least one of a KLdivergence or Bayes probability theorem.
 7. The computer-implementedmethod of claim 1, wherein generating one or more content areas in whichto display the topical content further comprises dynamically generatingone or more content areas on the website.
 8. The computer-implementedmethod of claim 1, wherein generating one or more content areas in whichto display the topical content further comprises dynamically generatingone or more subsections of the website.
 9. The computer-implementedmethod of claim 1, wherein updating the one or more navigational menusand links of the website further comprises dynamically updating ataxonomy of the website.
 10. The computer-implemented method of claim 1,wherein the factors comprise one or more of an IP address, orlocation-based attributes associated with the users.
 11. A system forpresenting topical content on a website for users, the systemcomprising: at least one processor; and a storage device storing a setof instructions, that when executed by the at least one processor,causes the at least one processor to: retain, in a database, attributesof a plurality of users, wherein the attributes comprise at least oneof: an impression history, a purchase history, a conversion history,and/or user preferences; associate a plurality of users with a pluralityof factors including the attributes; associate collected electroniccontent with a plurality of topics; determine levels of popularitycorresponding to combinations of the factors and the topics based on thefactors including the attributes, wherein the levels of popularityinclude a higher level and a lower level; receive, from a device of afirst user, a content request associated with a first one of thefactors; parsing one or more websites for content associated with therequest; caching the one or more parsed websites; determine, based onthe popularity of the topics in the higher level, discounted levels ofpopularity corresponding to the popularity of the topics in the lowerlevel and the first one of the factors; manage the topical content basedon the discounted levels of popularity for the first one of the factorsand further generate one or more content areas in which to display thetopical content; and generate instructions to present, on the website,one or more pieces of the managed topical content in the generated oneor more content areas; wherein managing the topical content comprisesupdating one or more navigational menus and links of the website basedon the discounted levels of popularity for the first ones of thefactors, and wherein generating the instructions includes generatinginstructions to update the one or more navigational menus and links ofthe website.
 12. The system of claim 11, wherein the instructions arefurther executed by the at least one processor to: receive, from theplurality of users, selections of content from the collected electroniccontent; and determine the levels of popularity, for combinations of thetopics and the factors, based on the numbers of times users associatedwith the factors selected content associated with the topics.
 13. Thesystem of claim 11, wherein the instructions are further executed by theat least one processor to: determine a second one of the factors; andcalculate the discounted levels of popularity for the topics based on(i) the levels of popularity corresponding to the combination of thetopics and the first one of the factors, and (ii) the levels ofpopularity corresponding to the combination of the topics and the secondone of the factors.
 14. The system of claim 13, wherein the second oneof the factors encompasses the first one of the factors.
 15. The systemof claim 13, wherein at least one of the first one of the factors andthe second one of the factors is time.
 16. The system of claim 13,wherein the instructions are further executed by the at least oneprocessor to calculate the discounted levels of popularity using atleast one of a KL divergence or Bayes probability theorem.
 17. Thesystem of claim 11, wherein generating one or more content areas inwhich to display the topical content further comprises dynamicallygenerating one or more content areas on the website.
 18. The system ofclaim 11, wherein generating one or more content areas in which todisplay the topical content further comprises dynamically generating oneor more subsections of the website.
 19. The system of claim 11, whereinthe one or more navigational menus and links of the website furthercomprises dynamically updating a taxonomy of the website.
 20. The systemof claim 11, wherein the factors comprise one or more of an IP address,or one or more location-based attributes associated with the users. 21.A non-transitory computer-readable storage medium storing a set ofinstructions executable by a processor to perform a method forpresenting topical content on a website for users, the methodcomprising: retaining, in a database, attributes of a plurality ofusers, wherein the attributes comprise at least one of: an impressionhistory, a purchase history, a conversion history, and/or userpreferences; associating a plurality of users with a plurality offactors including the attributes; associating collected electroniccontent with a plurality of topics; determining levels of popularitycorresponding to combinations of the factors and the topics based on thefactors including the attributes, wherein the levels of popularityinclude a higher level and a lower level; receiving, from a device of afirst user, a content request associated with a first one of thefactors; parsing one or more websites for content associated with therequest; caching the one or more parsed websites; determining, based onthe popularity of the topics in the higher level, one or more discountedlevels of popularity corresponding to the popularity of the topics inthe lower level and the first one of the factors; managing the topicalcontent based on the one or more discounted levels of popularity for thefirst one of the factors and further generating one or more contentareas in which to display the topical content; and generatinginstructions to present, on the website, one or more pieces of themanaged topical content in the generated one or more content areas;wherein managing the topical content comprises updating one or morenavigational menus and links of the website based on the discountedlevels of popularity for the first ones of the factors, and whereingenerating the instructions includes generating instructions to updatethe one or more navigational menus and links of the website.